Estimating the applicability of passive house standards in Mediterranean climate conditions with neuro fuzzy logic and its including into the design process: A case of a semi-olympic indoor pool

Passive House is an energy-saving construction concept that is decided during the design phase of the building or can be applied to existing buildings. Passive House, which is widely used in countries with cold climates, has started to be applied in hot climates only for small-scale buildings in recent years. This concept, which has not been applied in large-scale spaces in hot climates before, is being investigated to alleviate the heating and cooling load and its applicability. Within the scope of the study, a case study will be made for the province of Antalya, which has Mediterranean climate conditions, for the applicability of the indoor pool structure with the Passive House model in hot climates. Although this study produces results for the Mediterranean climate regions of Turkey, an exemplary guide is created for both Turkey's other climates and indoor pool structures in other countries. In this context, the data obtained by the artificial intelligence method and neural fuzzy logic technique give direction to the architectural design, the window-to-wall ratio, the presence of shading elements on the façade, the thermal transmittance values of the building elements, and the orientation of the building, depending on parameters such as the energy need of the variables to be provided at the lowest level. puts it. With the data obtained, many results have emerged for the most appropriate model for a large-scale building. By determining the direction of the building, finding the window-to-wall ratio according to whether there is a need for ventilation or shading, and choosing the building materials for the construction, it is ensured that the guiding parameters for the architectural design are created. Since it is difficult to make multi-criteria selections, the neural fuzzy logic method facilitates this decision-making process with the adaptive network-based fuzzy inference system (ANFIS), and it is an innovation in the literature to use the neural fuzzy logic method in architectural design. The accuracy rate of the model that emerged in the study was determined to be 0.9997 according to the regression analysis between the real data and ANFIS. In this case, it shows that the accuracy rate is 99%. It has been determined that a large-scale structure provides high energy efficiency in cases where the building is oriented north, south, east or west and the window and wall ratios are 10% and 90%. It has also been determined with the obtained data that the use of insulation in the materials to be selected in the construction of the building has a significant contribution to energy efficiency. The thermal transmittance value of the building elements and the window glass properties were also investigated in terms of compliance with the Passive House concept in architectural design and the effect of heat loss rates was investigated by making calculations according to the TS 825 Thermal Insulation Rules in Buildings standard and making comparisons according to the floor height, space size, and window wall ratios in the building. With the application of the obtained results to the indoor pool structure that continues to operate in Antalya, the cost calculation of electricity and natural gas expenses shows that approximately 60% profit can be made in the winter period and approximately 15% in the summer period. With this study, information is provided to correct the deficiencies in construction, especially in the Mediterranean climate of Turkey.